Sewage sludge from wastewater treatment plants is an important alternative to chemical fertilizers for agricultural use due to its nutrient-rich structure and organic matter content. However, the presence of toxic components (heavy metals, pathogens and persistent organic pollutants) in sewage sludge limits its direct use due to health and environmental risks. Thus, safe processing and effective management techniques are necessary for sludge reuse in agriculture in a sustainable manner. This review examines recent technological advancements that enhance the safe and efficient use of sewage sludge in agriculture. Emphasis is placed on innovative treatment and stabilization methods, such as thermal hydrolysis, anaerobic digestion, and biochar production, which improve nutrient recovery and reduce pathogen and heavy metal risks. Machine learning algorithms are being employed for the real-time prediction of heavy metal concentrations and the overall ecological risk associated with land application. Furthermore, Artificial intelligence (AI) driven soft sensors and optimization models are crucial for controlling operational parameters like sludge retention time, improving process efficiency, and ensuring the final product meets stringent regulatory standards for biosolid application. Ultimately, this review underscores that moving beyond conventional sludge disposal requires integrating cutting-edge recovery technologies with AI-based predictive and control systems to realize a true circular bioeconomy in sludge management.
Agriculture Artificial Intelligence Environmental Risk Machine Learning Sewage Sludge Sustainability Wastewater Treatment Plants
| Primary Language | English |
|---|---|
| Subjects | Environmental Rehabilitation and Restoration |
| Journal Section | Review Article |
| Authors | |
| Submission Date | October 21, 2025 |
| Acceptance Date | December 5, 2025 |
| Publication Date | December 28, 2025 |
| Published in Issue | Year 2025 Volume: 9 Issue: Special |
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